DocumentCode
2510088
Title
Solving capacitated vehicle routing problem based on improved genetic algorithm
Author
Jie-sheng, Wang ; Chang, Liu ; Ying, Zhang
Author_Institution
Sch. of Electron. & Inf. Eng., Liaoning Univ. of Sci. & Technol., Anshan, China
fYear
2011
fDate
23-25 May 2011
Firstpage
60
Lastpage
64
Abstract
Aiming at the capacitated vehicle routing problem (CVRP) in the matter stream delivery field, an improved genetic algorithm (GA) based on local mutation operator is adopted. Two layers chromosome coding scheme is designed which can improve initial solutions. This coding method can insure that the sub-routing is effective to satiety the vehicle capacitated constraints. These improved measures have important significance to depress procedural intricacy degree, advance convergence of algorithm velocity and algorithmic local search ability. The simulation experiment results show the improved genetic algorithm compared with BGA can achieve better optimization results and has better efficiency to solve CVRP.
Keywords
genetic algorithms; logistics; road traffic; CVRP; advance convergence; algorithm velocity; algorithmic local search ability; capacitated vehicle routing problem; chromosome coding scheme; genetic algorithm; local mutation operator; matter stream delivery field; vehicle capacitated constraints; Biological cells; Encoding; Genetic algorithms; Genetics; Routing; Search problems; Vehicles; Capability Vehicle Routing Problem; Genetic Algorithm; Local Mutation; Two Layers Chromosome;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Decision Conference (CCDC), 2011 Chinese
Conference_Location
Mianyang
Print_ISBN
978-1-4244-8737-0
Type
conf
DOI
10.1109/CCDC.2011.5968146
Filename
5968146
Link To Document